run_tsne: Run tSNE
In jmonlong/scCNAutils: Functions to analyze copy number aberrations in single-cell data
run_tsne R Documentation
Run tSNE
Description
tSNE from PCA results.
Usage
run_tsne(pca_o, nb_pcs = 10, nb_it = 1000, tsne_init = NULL, seed = 999)
Arguments
pca_o
the output of run_pca
nb_pcs
the number of PCs to use. Default 10.
nb_it
the number of iterations. Default 1000.
tsne_init
previous tSNE results to use as starting point. Not used is NULL (default).
seed
the seed for the random generator.
Value
a data.frame with columns: cell, tsne1, tsne2
Author(s)
Jean Monlong
jmonlong/scCNAutils documentation built on May 3, 2022, 4:34 a.m.
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| run_tsne | R Documentation |
Run tSNE
Description
tSNE from PCA results.
Usage
run_tsne(pca_o, nb_pcs = 10, nb_it = 1000, tsne_init = NULL, seed = 999)
Arguments
pca_o |
the output of |
nb_pcs |
the number of PCs to use. Default 10. |
nb_it |
the number of iterations. Default 1000. |
tsne_init |
previous tSNE results to use as starting point. Not used is NULL (default). |
seed |
the seed for the random generator. |
Value
a data.frame with columns: cell, tsne1, tsne2
Author(s)
Jean Monlong
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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